机器人实战案例

工业机器人控制系统是工业自动化的核心，需要实现精确的运动控制、 轨迹规划和任务调度。本案例展示了一个基于ROS的工业机器人控制系统。

import rospy
from moveit_commander import MoveGroupCommander
from geometry_msgs.msg import Pose
import numpy as np

class IndustrialRobot:
    def __init__(self):
        rospy.init_node('industrial_robot_control')
        self.arm = MoveGroupCommander("manipulator")
        self.gripper = MoveGroupCommander("gripper")
        
    def move_to_position(self, x, y, z):
        pose_target = Pose()
        pose_target.position.x = x
        pose_target.position.y = y
        pose_target.position.z = z
        self.arm.set_pose_target(pose_target)
        self.arm.go(wait=True)
        
    def pick_and_place(self, pick_pose, place_pose):
        # 移动到抓取位置
        self.move_to_position(*pick_pose)
        # 抓取物体
        self.gripper.set_named_target("close")
        self.gripper.go(wait=True)
        # 移动到放置位置
        self.move_to_position(*place_pose)
        # 释放物体
        self.gripper.set_named_target("open")
        self.gripper.go(wait=True)
        
    def execute_trajectory(self, waypoints):
        for point in waypoints:
            self.move_to_position(*point)
            rospy.sleep(0.5)

视觉引导装配系统结合了机器视觉和机器人控制，实现高精度的零件装配。 系统通过视觉识别零件位置，引导机器人完成装配任务。

import cv2
import numpy as np
from industrial_robot import IndustrialRobot

class VisionGuidedAssembly:
    def __init__(self):
        self.robot = IndustrialRobot()
        self.camera = cv2.VideoCapture(0)
        
    def detect_part(self, image):
        # 图像预处理
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        blur = cv2.GaussianBlur(gray, (5, 5), 0)
        
        # 边缘检测
        edges = cv2.Canny(blur, 50, 150)
        
        # 轮廓检测
        contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        
        # 找到最大轮廓
        if contours:
            max_contour = max(contours, key=cv2.contourArea)
            M = cv2.moments(max_contour)
            if M["m00"] != 0:
                cx = int(M["m10"] / M["m00"])
                cy = int(M["m01"] / M["m00"])
                return (cx, cy)
        return None
        
    def assemble_parts(self):
        while True:
            ret, frame = self.camera.read()
            if not ret:
                break
                
            part_position = self.detect_part(frame)
            if part_position:
                # 转换坐标到机器人坐标系
                robot_x, robot_y = self.transform_coordinates(part_position)
                # 执行装配
                self.robot.pick_and_place(
                    (robot_x, robot_y, 0.1),
                    (robot_x + 0.1, robot_y, 0.1)
                )